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""" |
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Extract all MVP tasks from full_plan.md and create comprehensive batch file for GitHub issues. |
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This script systematically extracts tasks from each MVP and sprint in the full plan. |
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""" |
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import json |
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from typing import Any |
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def extract_mvp_tasks(): |
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"""Extract all MVP tasks from full_plan.md.""" |
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with open("full_plan.md", encoding="utf-8") as f: |
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content = f.read() |
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mvp_tasks = {} |
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mvp_tasks[1] = { |
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"name": "KG-Powered Tool Suggester", |
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"duration": "Day 1-2", |
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"sprints": [ |
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{ |
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"sprint": 1, |
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"name": "Foundation & Core Components", |
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"tasks": [ |
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{ |
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"id": "KG_Structure", |
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"name": "Create in-memory Knowledge Graph structure", |
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"description": "Implement InMemoryKG class for storing MCP Tool metadata and embeddings", |
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}, |
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{ |
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"id": "Tool_Data_Loading", |
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"name": "Load initial MCP Tools from JSON", |
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"description": "Load 3-5 diverse tools into KG with structured and vector storage", |
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}, |
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{ |
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"id": "Embedder_Service", |
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"name": "Implement embedding generation service", |
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"description": "Create EmbeddingService using LLM APIs for tool descriptions", |
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}, |
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{ |
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"id": "Semantic_Search", |
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"name": "Implement cosine similarity search", |
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"description": "Add vector search for finding relevant tools based on query embeddings", |
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}, |
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{ |
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"id": "Simple_Planner", |
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"name": "Create SimplePlannerAgent", |
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"description": "Agent that embeds queries and searches for relevant tools", |
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}, |
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{ |
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"id": "Basic_Gradio_UI", |
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"name": "Build basic Gradio interface", |
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"description": "UI with query input and tool suggestions display", |
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}, |
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], |
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} |
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], |
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} |
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mvp_tasks[2] = { |
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"name": "KG Suggests Actionable Tool with Prompt Template", |
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"duration": "Day 2-3", |
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"sprints": [ |
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{ |
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"sprint": 1, |
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"name": "Prompt Integration", |
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"tasks": [ |
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{ |
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"id": "Prompt_Ontology", |
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"name": "Define MCPPrompt dataclass", |
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"description": "Extend KG to store prompt templates with tool linkage", |
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}, |
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{ |
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"id": "Prompt_Data_Loading", |
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"name": "Load initial prompts from JSON", |
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"description": "Link prompt templates to tools in the KG", |
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}, |
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{ |
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"id": "Enhanced_Planner", |
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"name": "Enhance planner for tool+prompt selection", |
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"description": "Select both tools and associated prompts based on query", |
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}, |
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{ |
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"id": "UI_Prompt_Display", |
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"name": "Update UI to display prompt templates", |
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"description": "Show selected prompt templates with placeholders", |
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}, |
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{ |
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"id": "PlannedStep_Structure", |
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"name": "Create PlannedStep dataclass", |
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"description": "Represent tool+prompt selections", |
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}, |
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], |
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} |
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], |
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} |
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mvp_tasks[3] = { |
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"name": "Interactive Prompt Filling & Simulated Execution", |
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"duration": "Day 3-4", |
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"sprints": [ |
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{ |
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"sprint": 1, |
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"name": "Dynamic UI Generation", |
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"tasks": [ |
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{ |
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"id": "Dynamic_Input_Fields", |
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"name": "Implement dynamic Gradio input field generation", |
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"description": "Generate interactive gr.Textbox components based on prompt variables", |
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}, |
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{ |
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"id": "Input_Collection", |
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"name": "Create user input collection mechanism", |
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"description": "Collect user inputs from dynamic fields", |
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}, |
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{ |
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"id": "UI_State_Management", |
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"name": "Implement UI state transitions", |
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"description": "Manage planning and execution phases", |
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}, |
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], |
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}, |
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{ |
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"sprint": 2, |
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"name": "User Input Collection", |
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"tasks": [ |
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{ |
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"id": "Input_Validation", |
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"name": "Add input validation for dynamic fields", |
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"description": "Validate inputs based on prompt requirements", |
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}, |
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{ |
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"id": "Stub_Executor", |
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"name": "Create StubExecutorAgent", |
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"description": "Basic simulate_execution method", |
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}, |
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{ |
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"id": "Execute_Button", |
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"name": "Add Execute Plan button", |
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"description": "Wire button to input collection", |
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}, |
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], |
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}, |
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{ |
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"sprint": 3, |
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"name": "Integrate Executor & Display Results", |
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"tasks": [ |
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{ |
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"id": "Tool_Specific_Mocks", |
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"name": "Enhance executor for tool-specific responses", |
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"description": "Return different mock responses based on tool_id", |
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}, |
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{ |
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"id": "Executor_Integration", |
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"name": "Integrate StubExecutorAgent into app.py", |
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"description": "Wire executor into main workflow", |
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}, |
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{ |
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"id": "Result_Display", |
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"name": "Format and display simulated results", |
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"description": "Show execution results in UI", |
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}, |
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], |
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}, |
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{ |
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"sprint": 4, |
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"name": "Refine Simulated Outputs", |
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"tasks": [ |
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{ |
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"id": "Input_Aware_Mocks", |
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"name": "Make mock responses input-sensitive", |
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"description": "Generate responses based on user inputs", |
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}, |
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{ |
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"id": "Error_Simulation", |
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"name": "Add simulated error states", |
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"description": "Handle edge cases and failures", |
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}, |
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{ |
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"id": "UI_Polish", |
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"name": "Improve execution result display", |
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"description": "Better formatting and user experience", |
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}, |
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], |
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}, |
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{ |
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"sprint": 5, |
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"name": "MVP3 Finalization", |
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"tasks": [ |
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{ |
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"id": "E2E_Testing", |
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"name": "Comprehensive end-to-end testing", |
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"description": "Test MVP1-3 features integration", |
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}, |
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{ |
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"id": "Documentation_Update", |
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"name": "Update all READMEs for MVP3", |
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"description": "Document MVP3 functionality", |
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}, |
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{ |
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"id": "Code_Cleanup", |
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"name": "Final code review and cleanup", |
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"description": "Prepare MVP3 for deployment", |
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}, |
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], |
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}, |
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], |
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} |
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mvp_tasks[4] = { |
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"name": "Real MCP Tool Execution via Gradio Server", |
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"duration": "Day 4-5", |
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"sprints": [ |
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{ |
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"sprint": 1, |
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"name": "First MCP Server (Summarizer)", |
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"tasks": [ |
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{ |
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"id": "Summarizer_Project", |
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"name": "Create separate project for MCP Summarizer", |
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"description": "New project directory with environment setup", |
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}, |
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{ |
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"id": "Summarizer_Logic", |
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"name": "Implement text summarization", |
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"description": "Use HF Inference API for summarization", |
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}, |
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{ |
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"id": "Summarizer_MCP", |
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"name": "Create Gradio UI and MCP server", |
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"description": "Gradio app exposed as MCP server", |
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}, |
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{ |
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"id": "Summarizer_Deploy", |
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"name": "Deploy Summarizer to HF Space", |
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"description": "Live deployment with documentation", |
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}, |
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], |
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}, |
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{ |
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"sprint": 2, |
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"name": "Second MCP Server (Sentiment)", |
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"tasks": [ |
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{ |
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"id": "Sentiment_Project", |
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"name": "Create separate project for MCP Sentiment Analyzer", |
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"description": "New project directory with environment setup", |
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}, |
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{ |
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"id": "Sentiment_Logic", |
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"name": "Implement sentiment analysis", |
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"description": "Use HF Inference API for sentiment", |
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}, |
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{ |
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"id": "Sentiment_MCP", |
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"name": "Create Gradio UI and MCP server", |
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"description": "Gradio app exposed as MCP server", |
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}, |
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{ |
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"id": "Sentiment_Deploy", |
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"name": "Deploy Sentiment Analyzer to HF Space", |
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"description": "Live deployment with documentation", |
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}, |
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], |
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}, |
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{ |
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"sprint": 3, |
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"name": "Update Main KG & Executor", |
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"tasks": [ |
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{ |
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"id": "Tool_Ontology_Update", |
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"name": "Add execution_type field to MCPTool", |
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"description": "Distinguish live vs simulated tools", |
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}, |
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{ |
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"id": "Live_URLs_Update", |
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"name": "Update initial_tools.json with live URLs", |
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"description": "Point to deployed MCP server endpoints", |
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}, |
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{ |
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"id": "MCP_Executor", |
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"name": "Refactor executor for real HTTP calls", |
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"description": "Make actual calls to live MCP servers", |
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}, |
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{ |
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"id": "Error_Handling", |
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"name": "Implement robust error handling", |
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"description": "Handle network failures and parsing errors", |
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}, |
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], |
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}, |
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{ |
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"sprint": 4, |
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"name": "E2E Testing & UI Polish", |
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"tasks": [ |
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{ |
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"id": "Live_Testing", |
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"name": "Test live MCP tool integration", |
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"description": "End-to-end testing with real tools", |
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}, |
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{ |
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"id": "UI_Live_Indicator", |
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"name": "Differentiate live vs simulated results", |
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"description": "Visual indicators in UI", |
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}, |
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{ |
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"id": "Error_Display", |
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"name": "Improve display of live MCP errors", |
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"description": "User-friendly error messaging", |
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}, |
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], |
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}, |
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{ |
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"sprint": 5, |
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"name": "Final Documentation & Submission", |
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"tasks": [ |
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{ |
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"id": "Track1_Documentation", |
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"name": "Update all READMEs for MVP4", |
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"description": "Document live tool integration", |
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}, |
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{ |
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"id": "Demo_Videos", |
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"name": "Record demo videos", |
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"description": "Main demo and Track 1 tool demos", |
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}, |
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{ |
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"id": "HF_Spaces_Final", |
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"name": "Finalize all HF Spaces", |
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"description": "Configure secrets, tags, READMEs", |
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}, |
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], |
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}, |
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], |
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} |
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mvp_tasks[5] = { |
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"name": "KG-Informed Model Preferences for Sampling", |
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"duration": "Day 5-6", |
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"sprints": [ |
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{ |
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"sprint": 1, |
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"name": "Enhance KG Ontology for Model Preferences", |
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"tasks": [ |
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{ |
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"id": "Sampling_Ontology", |
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"name": "Add sampling preference fields to MCPPrompt", |
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"description": "Model hints, cost/speed/intelligence priorities", |
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}, |
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{ |
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"id": "Sampling_Data", |
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"name": "Update initial_prompts.json with preferences", |
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"description": "Add diverse sampling preferences to prompts", |
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}, |
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{ |
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"id": "KG_Loading_Update", |
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"name": "Update InMemoryKG loading for new fields", |
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"description": "Load sampling preference metadata", |
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}, |
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], |
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}, |
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{ |
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"sprint": 2, |
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"name": "Planner Logic for Sampling Requests", |
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"tasks": [ |
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{ |
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"id": "Sampling_Construction", |
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"name": "Implement sampling request construction", |
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"description": "Generate MCP sampling/createMessage params from KG", |
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}, |
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{ |
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"id": "Model_Preferences", |
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"name": "Populate modelPreferences dynamically", |
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"description": "Use KG data to set model hints and priorities", |
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}, |
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{ |
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"id": "Sampling_Agent_Logic", |
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"name": "Add sampling logic to planner agent", |
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"description": "Method to construct conceptual sampling requests", |
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}, |
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], |
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}, |
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{ |
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"sprint": 3, |
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"name": "Gradio UI for Sampling Requests", |
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"tasks": [ |
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{ |
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"id": "Sampling_UI_Elements", |
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"name": "Add sampling UI components", |
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"description": "Button and JSON display for sampling requests", |
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}, |
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{ |
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"id": "Sampling_Handler", |
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"name": "Implement sampling request handler", |
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"description": "Gradio handler to trigger and display sampling JSON", |
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}, |
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{ |
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"id": "Sampling_Integration", |
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"name": "Wire sampling button to backend", |
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"description": "Connect UI to sampling construction logic", |
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}, |
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], |
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}, |
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{ |
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"sprint": 4, |
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"name": "LLM Refinement (Optional)", |
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"tasks": [ |
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{ |
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"id": "LLM_Refinement_Logic", |
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"name": "Add LLM refinement suggestions", |
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"description": "Use LLM to suggest model hints based on preferences", |
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}, |
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{ |
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"id": "Refinement_UI", |
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"name": "Display LLM refinement in UI", |
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"description": "Show LLM-generated suggestions", |
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}, |
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{ |
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"id": "Chat_Completion_Service", |
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"name": "Extend EmbeddingService for chat", |
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"description": "Add chat completion capability", |
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}, |
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], |
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}, |
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{ |
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"sprint": 5, |
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"name": "Final Testing & Innovation Demo", |
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"tasks": [ |
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{ |
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"id": "Sampling_Testing", |
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"name": "Test conceptual sampling features", |
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"description": "Validate sampling request generation", |
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}, |
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{ |
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"id": "Innovation_Documentation", |
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"name": "Update READMEs for innovation showcase", |
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"description": "Highlight innovative MCP usage", |
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}, |
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{ |
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"id": "Final_Submission_Prep", |
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"name": "Final hackathon submission preparation", |
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"description": "Videos, docs, CI checks", |
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}, |
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], |
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}, |
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], |
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} |
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return mvp_tasks |
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def create_github_batch_file(mvp_tasks: dict[int, Any]): |
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"""Create a comprehensive batch file for GitHub issue creation.""" |
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|
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batch_content = """# KGraph-MCP MVP Tasks - Complete Extraction from full_plan.md |
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# Format: MVP|Sprint|Name|Objective |
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# This file contains ALL tasks from the comprehensive 5-MVP plan |
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""" |
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|
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task_list = [] |
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|
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for mvp_num, mvp_data in mvp_tasks.items(): |
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batch_content += ( |
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f"\n# MVP {mvp_num}: {mvp_data['name']} ({mvp_data['duration']})\n" |
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) |
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for sprint_data in mvp_data["sprints"]: |
|
|
sprint_num = sprint_data["sprint"] |
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|
sprint_name = sprint_data["name"] |
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batch_content += f"# Sprint {sprint_num}: {sprint_name}\n" |
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|
|
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for task in sprint_data["tasks"]: |
|
|
task_line = f"{mvp_num}|{sprint_num}|{task['id']}|{task['description']}" |
|
|
batch_content += task_line + "\n" |
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|
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|
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task_list.append( |
|
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{ |
|
|
"mvp": mvp_num, |
|
|
"sprint": sprint_num, |
|
|
"name": task["id"], |
|
|
"title": task["name"], |
|
|
"description": task["description"], |
|
|
"objective": task["description"], |
|
|
} |
|
|
) |
|
|
|
|
|
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|
|
with open("full_plan_mvp_tasks_complete.txt", "w") as f: |
|
|
f.write(batch_content) |
|
|
|
|
|
|
|
|
with open("full_plan_mvp_tasks_complete.json", "w") as f: |
|
|
json.dump(task_list, f, indent=2) |
|
|
|
|
|
print(f"✅ Created comprehensive batch file with {len(task_list)} tasks") |
|
|
print("📄 Files created:") |
|
|
print(" - full_plan_mvp_tasks_complete.txt (batch format)") |
|
|
print(" - full_plan_mvp_tasks_complete.json (detailed JSON)") |
|
|
|
|
|
return task_list |
|
|
|
|
|
|
|
|
def main(): |
|
|
"""Main extraction and batch creation function.""" |
|
|
print("🔍 Extracting MVP tasks from full_plan.md...") |
|
|
|
|
|
mvp_tasks = extract_mvp_tasks() |
|
|
task_list = create_github_batch_file(mvp_tasks) |
|
|
|
|
|
print("\n📊 Task Summary:") |
|
|
mvp_counts = {} |
|
|
for task in task_list: |
|
|
mvp = task["mvp"] |
|
|
mvp_counts[mvp] = mvp_counts.get(mvp, 0) + 1 |
|
|
|
|
|
for mvp, count in mvp_counts.items(): |
|
|
print(f" MVP {mvp}: {count} tasks") |
|
|
|
|
|
print("\n🎯 Next Steps:") |
|
|
print(" 1. Review the generated files") |
|
|
print( |
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" 2. Use 'just mvp-batch-create full_plan_mvp_tasks_complete.txt' to create GitHub issues" |
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) |
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print(" 3. Use 'just gh-sync-all' to sync with GitHub project") |
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if __name__ == "__main__": |
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main() |
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